A Hybrid Convolutional-Transformer Approach for Accurate Electroencephalography (EEG)-Based Parkinson's Disease Detection.
- DOI
- 10.3390/bioengineering12060583
- Published
- 2025 May 28
- Container
- Bioengineering (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/bioengineering12060583,
title = {A Hybrid Convolutional-Transformer Approach for Accurate Electroencephalography (EEG)-Based Parkinson's Disease Detection.},
author = {Bunterngchit C and Baniata LH and Albayati H and Baniata MH and Alharbi K and Alshammari FH and Kang S},
year = {2025},
journal = {Bioengineering (Basel, Switzerland)},
doi = {10.3390/bioengineering12060583},
url = {https://doi.org/10.3390/bioengineering12060583}
}RIS
TY - JOUR TI - A Hybrid Convolutional-Transformer Approach for Accurate Electroencephalography (EEG)-Based Parkinson's Disease Detection. AU - Bunterngchit C AU - Baniata LH AU - Albayati H AU - Baniata MH AU - Alharbi K AU - Alshammari FH AU - Kang S PY - 2025 JO - Bioengineering (Basel, Switzerland) DO - 10.3390/bioengineering12060583 UR - https://doi.org/10.3390/bioengineering12060583 ER -
APA
C, B., LH, B., H, A., MH, B., K, A., FH, A., & S, K. (2025). A Hybrid Convolutional-Transformer Approach for Accurate Electroencephalography (EEG)-Based Parkinson's Disease Detection.. Bioengineering (Basel, Switzerland). https://doi.org/10.3390/bioengineering12060583
Source records
- pubmed · retrieved 2026-09-27T11:19:38.936Z